New Trends in Laser Scanning for Cultural Heritage

Balado, Jesús; Frías, Ernesto; González-Collazo, Silvia María; Díaz-Vilariño, L.

doi:10.1007/978-981-19-1894-0_10

Cited by 10 publications

(2 citation statements)

References 39 publications

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“…The rest of the spaces have been tested according to size, solar lighting, and some equipment similar to the station environment. Based on each environment scanned with the smartphone, we collected different deviations (distributed between 0–2 cm, 2–5 cm, 5–10 cm, and >10 cm) of the points from the FARO static scanner data as reference [ 29 , 37 , 38 ]. This deviation is determined by using the cloud-to-cloud (C2C) distance analysis on CloudCompare that calculates distance of two-point cloud data with one considered as the reference cloud and the other as the compared cloud.…”

Section: Methodsmentioning

confidence: 99%

Smartphone LiDAR Data: A Case Study for Numerisation of Indoor Buildings in Railway Stations

Catharia

Richard

Vignoles

et al. 2023

Sensors

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The combination of LiDAR with other technologies for numerisation is increasingly applied in the field of building, design, and geoscience, as it often brings time and cost advantages in 3D data survey processes. In this paper, the reconstruction of 3D point cloud datasets is studied , through an experimental protocol evaluation of new LiDAR sensors on smartphones. To evaluate and analyse the 3D point cloud datasets, different experimental conditions are considered depending on the acquisition mode and the type of object or surface being scanned. The conditions allowing us to obtain the most accurate data are identified and used to propose which acquisition protocol to use. This protocol seems to be the most adapted when using these LiDAR sensors to digitise complex interior buildings such as railway stations. This paper aims to propose: (i) a methodology to suggest the adaptation of an experimental protocol based on factors (distance, luminosity, surface, time, and incidence) to assess the precision and accuracy of the smartphone LiDAR sensor in a controlled environment; (ii) a comparison, both qualitative and quantitative, of smartphone LiDAR data with other traditional 3D scanner alternatives (Faro X130, VLX, and Vz400i) while considering three representative building interior environments; and (iii) a discussion of the results obtained in a controlled and a field environment, making it possible to propose recommendations for the use of the LiDAR smartphone at the end of the numerisation of the interior space of a building.

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Section: Methodsmentioning

confidence: 99%

Smartphone LiDAR Data: A Case Study for Numerisation of Indoor Buildings in Railway Stations

Catharia

Richard

Vignoles

et al. 2023

Sensors

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“…UAVs equipped with high-resolution cameras are widely employed for large-scale mapping rooted in photogrammetric principles. Despite this progress, the 3D digital model lacks vital information, such as doors and windows, impacting its usability and potential applications within the Architecture, Engineering, and Construction domain [8,9].…”

Section: Introductionmentioning

confidence: 99%

Low-Cost Data, High-Quality Models: A Semi-Automated Approach to LOD3 Creation

Harshit,

Chaurasia,

Zlatanova

et al. 2024

IJGI

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In the dynamic realm of digital twin modeling, where advancements are swiftly unfolding, users now possess the unprecedented ability to capture and generate geospatial data in real time. This article delves into a critical exploration of this landscape by presenting a meticulously devised workflow tailored for the creation of Level of Detail 3 (LOD3) models. Our research methodology capitalizes on the integration of Apple LiDAR technology alongside photogrammetric point clouds acquired from Unmanned Aerial Vehicles (UAVs). The proposed process unfolds with the transformation of point cloud data into Industry Foundation Classes (IFC) models, which are subsequently refined into LOD3 Geographic Information System (GIS) models leveraging the Feature Manipulation Engine (FME) workbench 2022.1.2. This orchestrated synergy among Apple LiDAR, UAV-derived photogrammetric point clouds, and the transformative capabilities of the FME culminates in the development of precise LOD3 GIS models. Our proposed workflow revolutionizes this landscape by integrating multi-source point clouds, imbuing them with accurate semantics derived from IFC models, and culminating in the creation of valid CityGML LOD3 buildings through sophisticated 3D geometric operations. The implications of this technical innovation are profound. Firstly, it elevates the capacity to produce intricate infrastructure models, unlocking new vistas for modeling digital twins. Secondly, it extends the horizons of GIS applications by seamlessly integrating enriched Building Information Modeling (BIM) components, thereby enhancing decision-making processes and facilitating more comprehensive spatial analyses.

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